Oracle Select AI Agent is architected around four foundational behaviors: Planning, Tool Use, Reflection, and Memory Management . Oracle documentation describes these as the framework's principal layers. Planning interprets the user's objective, decomposes it into ordered actions, and identifies appropriate capabilities. Tool Use invokes mechanisms such as NL2SQL, RAG, PL/SQL procedures, or external REST services. Reflection evaluates observations returned by those tools and determines whether the current plan should continue, be revised, or use another capability. Memory preserves context and useful information, supporting coherent multi-turn interactions and longer-term continuity.

Oracle explicitly states that Select AI Agent combines planning, tool use, reflection, and memory and implements a ReAct-style agentic pattern in which the agent reasons, acts through tools, evaluates observations, and continues toward the goal.

The alternative answer sets describe generic information-retrieval or operational lifecycle stages but do not correspond to Oracle's defined Select AI Agent architecture. Consequently, B reproduces the four documented agent behaviors and is the correct answer in the supplied question set.

Study Guide reference/topic: Agentic AI for Oracle AI Database — Select AI Agent architecture, Planning, Tool Use, Reflection, Memory, and ReAct.

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